In this paper, we propose a personalized recommendation system for mobile
application software (app) to mobile user using semantic relations of apps consumed
by users. To do that, we define semantic relations between apps consumed by a
specific member and his/her social members using Ontology. Based on the relations,
we identify the most similar social members from the reasoning process. The reasoning
is explored from measuring the common attributes between apps consumed by
the target member and his/her social members. The more attributes shared by them,
the more similar is their preference for consuming apps.We also develop a prototype
of our system using OWL (Ontology Web Language) by defining ontology-based
semantic relations among 50 mobile apps. Using the prototype, we showed the feasibility
of our algorithm that our recommendation algorithm can be practical in the real
field and useful to analyze the preference of mobile user.